Biology and the Built Environment Center, University of Oregon, Eugene, Oregon, USAEnergy Studies in Buildings Laboratory, University of Oregon, Eugene, Oregon, USAInstitute for Health in the Built Environment, University of Oregon, Portland, Oregon, USA

Biology and the Built Environment Center, University of Oregon, Eugene, Oregon, USAInstitute for Health in the Built Environment, University of Oregon, Portland, Oregon, USAInstitute of Ecology & Evolution, University of Oregon, Eugene, Oregon, USASanta Fe Institute, Santa Fe, New Mexico, USA

Biology and the Built Environment Center, University of Oregon, Eugene, Oregon, USAEnergy Studies in Buildings Laboratory, University of Oregon, Eugene, Oregon, USAInstitute for Health in the Built Environment, University of Oregon, Portland, Oregon, USA

Relationships between biocide concentrations and microbial species. (a) Spearman correlations between microbial species and triclosan (TCS) or triclocarban (TCC) concentrations (ng g−1 dust), with significance as determined by HAllA (see Materials and Methods). The margin shows species’ occurrence frequencies for subjects in the Expanded Human Microbiome Project (35). (b) Number of resistance modules annotated in the pangenomes of species in the rows of panel a. Modules are members of the “Drug resistance” and “Drug efflux transporter/pump” KEGG (38) categories. The size of each bubble is scaled proportionally to the fraction of rooms in which both species-specific marker genes (i.e., the results of MetaPhlAn2 [50]) and the drug resistance gene were detected.

Enrichment of microbial functions with elevated triclosan. (a) Overrepresented functional capabilities among triclosan-related species (results of GSEA [42, 43]). Significantly overrepresented modules are grouped based on KEGG (38) functional categories. (b) Positive relationships between log2 1 + x-transformed gene copies per million (CPM) and triclosan levels (ng g−1 dust) for the most enriched module, the mtrAB transcriptional regulators. Bars represent individual rooms, stratified based on the proportions of species-specific annotations. Marker colors for triclosan levels are the same as in Fig. 1d. (c and d) Bar plots as in panel b for the two functions with the highest positive Spearman rank correlation coefficients with triclosan (ρ = 0.29 and 0.23, respectively).

Building groupings based on culture density, diversity, and drug resistance phenotypes. (a) Mean triclosan concentrations (error bars ± 2 SEM) per building level, with colors as in Fig. 1d. Median and quartiles are shown for a large significant cluster of similar buildings (identified in panels b and c). (b) Colony-forming unit (CFU) densities g−1 dust and the fractions of CFUs resistant to clarithromycin, ampicillin, and tetracycline. (c) Cluster dendrogram showing Gower dissimilarities between buildings based on features of their culturable communities. Blocks mark clusters with significant support (P < 0.01), based on 104 multiscale bootstrap resamples (45) of normalized feature values. The only cluster with significant support that consisted of more than three buildings is marked by a thick blue block and a colored star.

Supplemental Material

FIG S1

Features of the facilities’ occupancy, ventilation, and building material composition. (a to d) The proportions of sampled rooms from each (a) city and (b) space type and with (c) exterior-facing doors and (d) different flooring materials. Features of the facilities’ occupancy, ventilation, and building material composition were quantified using a combination of censuses, member sign-in records, and interviews with facility employees. (e to h) Distributions of (e) person visits day−1 m−2, (f) the number of functional moisture sources m−2 (e.g., water fountains, sinks), (g) the mean number of business hours day−1, and (h) the fraction of total business hours with open windows (dimensionless). Download FIG S1, EPS file, 1.3 MB.

TABLE S1

Results of ANOVA tests between indoor antimicrobial chemical concentrations and building features. Columns show linear correlation coefficients between centered and scaled antimicrobial chemicals (columns) and building features (rows); well-powered building features were retained for analysis using the entropy filter described in Methods and Materials. Column labels identify the chemicals to which statistics relate. Asterisks mark significance at the P < 0.05 and P < 0.01 levels. Download Table S1, PDF file, 0.1 MB.

FIG S2

Distributions and putative origins of microorganisms in athletic facilities. (a) Relationship between building occupancy (the fraction of buildings in which a species was detected) and mean relative abundances (±2 SEM) for species detected at least five times across our data set. A horizontal dashed line marks the occupancy threshold to be considered a member of the “core” microbiome, based on the definition by Lloyd-Price et al. (Nature 550:61–66, 2017, https://doi.org/10.1038/nature23889). Large points above this dashed line comprise species in the athletic facility “core,” which included Propionibacterium acnes, Pseudomonas sp., Massilia sp., C2-like viruses, Subdoligranulum sp., and Enhydrobacter aerosaccus, respectively. Points are colored based on the fraction of subjects in the Expanded Human Microbiome Project (HMP; J. Lloyd-Price et al., Nature 550:61–66, 2017, https://doi.org/10.1038/nature23889) on which they could be detected. A black line shows the fit from a smooth LOESS regression. (b) Meta-analysis of the present buildings, together with subjects from the Expanded HMP using principal-coordinate analysis (PCoA) of species’ relative abundances as described in the main text. Small colored points are microbial communities from HMP subjects colored by body site. Large gray points represent microbial communities from the present set of buildings. (c) Results of microbial source tracking (SourceTracker v1.0; D. Knights et al., Nat Methods 8:761, 2011, https://doi.org/10.1038/nmeth.1650). SourceTracker was trained on HMP samples (b), and predictions were generated by testing the trained model on microbial communities from the present set of buildings. (d) Distribution of phyla across samples; bars represent individual rooms and are ordered based on space type (x axis) and the proportions of Proteobacteria, which were the most abundant phylum, on average. Download FIG S2, PDF file, 2.1 MB.

TABLE S2

Groupings of built environment features into dissimilarity matrices. Variable groupings used as input to multiple regression on distance matrix (MRM) analysis. “Dissimilarity category” indicates the group label referred to in the main text. These groups contained sets of variables that are indicated in the “Variable” column; units for these covariates are provided in the “Units” column. Download Table S2, DOCX file, 0.1 MB.

DATA SET S1

Cleaning product ingredient census. Rows represent binary variables representing the presence or absence of chemical ingredients. Values of 1 indicate that the chemical in the row is included in at least one cleaning product routinely used by each facility’s cleaning staff. Columns correspond to individual rooms in each facility. Download Data Set S1, CSV file, 0.01 MB.